Conference Agenda

Large-scale high-frequency data on residential electricity consumption offer substantial opportunities for firms and researchers. Such data support the development of innovative technologies that benefit both the supply and demand sides of electricity markets and enable the identification of key parameters underlying consumers' economic preferences. We study consumers' decisions about providing their electricity consumption data to third parties. We design a survey to elicit consumers’ choices and their willingness to accept (WTA) compensation for providing electricity data in an actual data transaction. To reveal how consumers are responsive to information about the benefits of sharing electricity consumption data, over 20,000 survey participants are randomly assigned to treatments that vary in the information provided. The results show that these information treatments discourage data sharing, suggesting that the information provided encourages consumers to retain control over their electricity data. However, the treatments do not significantly affect the distribution of elicited WTA among those who agree to provide their data. We reveal substantial selection effects in data provision by comparing attributes, such as risk preferences and peak electricity consumption, between participants who agree to provide their data, either with or without monetary compensation, and those who decline. Our findings underscore the importance for policymakers of understanding consumers' incentives to share electricity consumption data and of carefully applying results from previous studies that rely on such data.

This paper studies the behavior of residential energy consumption under block-tariff pricing, using high-frequency and billing data at the household level. We find that households primarily adjust their electricity demand in response to the average price they perceived, rather than the average or marginal prices. Such “information-driven” behaviors would cause cognitive bias and delayed responses to price changes, lead to significant over-consumption, and impact social welfare. Hence, providing clearer and more salient price information can therefore enhance policy effectiveness. Heterogeneous analysis further reveals that price responsiveness declines with household income and consumption levels. Regarding these facts, we suggest ``fewer blocks and higher gaps" pricing system balancing the policy target and efficiency.

Dynamic electricity tariffs may enhance welfare, especially in electricity markets with increasing shares of variable renewable energy sources. However, previous surveys and experiments suggest that consumers may be reluctant to adopt dynamic tariffs due to complexity and risk aversion. This article examines real-world consumer choices between a dynamic tariff, which features a fixed price during the first month and fluctuates with wholesale prices thereafter, and a fixed tariff, with a 12-month price guarantee. We exploit variations in time, space, and consumer size to estimate the effect of the first-month tariff cost difference on choice probabilities. We find that consumers without electric heating are willing to pay a 19--40\% premium for a fixed tariff during the first month, and consumers with electric heating tend to prefer fixed tariffs regardless of the premium. We discuss the role of transparency and risk management in enhancing the adoption of dynamic tariffs.

We study household acceptance of flexibility contracts for electric vehicles (EVs) and heat pumps (HPs), two key technologies for the energy transition. Using a survey and choice experiment with around 3,000 households, we analyze how contract design—particularly comfort limits such as indoor temperature or driving range—affects both the decision to participate and the flexibility households are willing to supply at different levels of remuneration. Around 70% of households in our sample are willing to participate. Discomfort affects utility nonlinearly for EVs: remaining range is

valued at close to €0/km above 100 km but rises to €0.40/km below, while HP flexibility is valued at about €2 per degree of indoor temperature reduction. We derive conditions under which flexibility contracts can achieve cost-effectiveness while remaining acceptable to households. Back-of-the envelope calculations suggest potential load reductions of up to 300 MW/event from HPs and 800 MW/event from EVs per million units.